Prevalence of Depression Symptoms and Associated Sociodemographic and Clinical Correlates Among Syrian Refugees in Lebanon

Prevalence of Depression Symptoms and
Associated Sociodemographic and Clinical
Correlates Among Syrian Refugees in Lebanon
Hady Naal
 Global Health Institute at the American University of Beirut
Dana Nabulsi
 Global Health Institute at the American University of Beirut
Nour El Arnaout
 Global Health Institute at the American University of Beirut
Lina Abdouni
 Global Health Institute at the American University of Beirut
Hani Dimassi
 Lebanese American University School of Pharmacy
Ranime Harb
 Lebanese American University School of Pharmacy
Shadi Saleh (  )
 Global Health Institute at the American University of Beirut

Research article

Keywords: Syrian Refugees, Informal Tented Settlements, Sijilli, Mental Health, Depression, Lebanon


License:   This work is licensed under a Creative Commons Attribution 4.0 International License.
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Background: Since the outbreak of the Syrian war in 2011, close to 6 million Syrian refugees have
escaped to Syria’s neighbouring countries, including Lebanon. Evidence suggests rising levels of mental
health disorders among Syrian refugee populations. Yet, to the best of our knowledge, large-scale studies
addressing the mental health of adult Syrian refugees in Lebanon are lacking.

Aims: We examined the prevalence of depression symptoms, which represent a common and debilitating
mental health disorder among Syrian refugee populations in Lebanon, along with their sociodemographic
and clinical correlates.

Methods: A cross-sectional survey design was conducted as part of a collaborative project-“Sijilli”- led by
the Global Health Institute at the American University of Beirut (Beirut, Lebanon) across 4 informal tented
settlements for refugees (Beirut, Bekaa, North, South) in Lebanon among adult Syrian refugees (≥18),
over a period extending from 2018 to 2020. The survey inquired about participants’ sociodemographic
and clinical characteristics, and screened participants for symptoms of depression through sequential
methodology using the Patient Health Questionnaire (PHQ-2 and PHQ-9).

Results: A total of 3255 adult Syrian refugees were enrolled in the study. Of those refugees, only 51.6%
(n=1678) screened positive on the PHQ-2 and were therefore eligible to complete the PHQ-9. The PHQ-9
analysis revealed high prevalence (25%) of moderate to severe depression in the total sample, suggestive
of high probability for major depression disorder (MDD). Further analyses indicate that being ≥45 years
of age (OR 1.70, 95% CI 1.22-2.36), a woman (OR 1.35, 95% CI 1.07-1.69), divorced/separated (OR 3.32,
95% CI 1.57-7.01), reporting a neurological (OR 1.77, 95% CI 1.20-2.61) or a mental health condition (OR
5.30, 95% CI 2.40-11.66) are major risk factors for MDD.

Conclusion: Our study suggests that one in four Syrian refugees in Lebanon have probable MDD, and our
 ndings have important public health and clinical implications on refugee health. There is a need to
enhance screening efforts, to improve access and referral to mental health services, and to improve post-
migration factors among Syrian refugees in Lebanon.

1. Introduction
The Syrian crisis has been widely described as one of the largest refugee crises of recent times (Nadim
Almoshmosh, Jefee Bahloul, Barkil-Oteo, Hassan, & Kirmayer, 2019; Hassan, Ventevogel, Jefee-Bahloul,
Barkil-Oteo, & Kirmayer, 2016). Close to 6 million Syrian refugees have ed to Syria’s neighbouring
countries, namely Lebanon, Jordan, Turkey, Egypt, and Iraq (UNHCR, 2018). Lebanon currently hosts over
1.5 million Syrian refugees, a number equivalent to 25% of its population (Refaat & Mohanna, 2013),
rendering it the country with the largest number of refugees per capita worldwide (Knudsen, 2016). The
massive in ux of Syrian refugees to Lebanon, coupled with their increased demand for healthcare
services, has signi cantly strained the country’s already fragile healthcare system, and has hindered its
ability to cater to their health needs (El Chammay & Ammar, 2014; E. Karam et al., 2016).
                                                 Page 2/25
Having escaped from con ict settings, refugees often experience a multitude of stressors such as
traumatic events, multiple forms of losses, discrimination, and acculturation di culties among others
during their journey of displacement (Hassan et al., 2016). They have therefore signi cantly higher odds
of developing mental health disorders compared to the general population (Hassan et al., 2016). Many
refugees are survivors of exploitation, torture, and sexual and gender-based violence, which further
exacerbate their vulnerability to health conditions (Hassan et al., 2016). That said, they are less likely to
receive mental health services because of social stigma, language and cultural barriers, imbalanced
power dynamics with service providers, limited access to services, and low mental health literacy,
including lack of perceived need (Abou-Saleh & Hughes, 2015; Hassan et al., 2016; Jefee-Bahloul,
Moustafa, Shebl, & Barkil-Oteo, 2014; Weine, 2011). Recent evidence indicates that mental health is one
of the most pressing health needs among Syrian refugees in Lebanon and neighbouring countries (El
Arnaout et al., 2019).

Major Depressive Disorder (MDD), Post-Traumatic Stress Disorder (PTSD), and other anxiety disorders
have been reported as the most common mental health disorders among Syrian refugees (Acarturk et al.,
2018; Georgiadou, Zbidat, Schmitt, & Erim, 2018), and they tend to be comorbid conditions. In the general
population, MDD in particular, is the third leading cause of years lived with disability (YLDs) (IHME, 2020),
and is considered a strong risk factor for suicide (May & Klonsky, 2016; Rogers, Ringer, & Joiner, 2018).
Therefore, depression warrants special attention among this population due to its long-term implications
that may impair social, individual, and vocational functioning, factors that are essential for survival,
productivity, and resettlement (Poole, Hedt-Gauthier, Liao, Raymond, & Bärnighausen, 2018; Ventevogel,
Van, Schilperoord, & Saxena, 2015). In one meta-analysis that included 24,051 refugees from multiple
nationalities pooled from international studies, 44% were found to have symptoms of depression (Lindert,
Ehrenstein, Priebe, Mielck, & Brähler, 2009). Despite certain limitations of that review, such as
heterogeneity of the included samples, this nding mirrors others in the literature addressing Syrian
refugees in Arab settings (Doocy, Sirois, Tileva, Storey, & Burnham, 2013; Jefee-Bahloul, Barkil-Oteo, Pless-
Mulloli, & Fouad, 2015; Llosa et al., 2014; Naja, Aoun, El Khoury, Abdallah, & Haddad, 2016). Furthermore,
previous reports from the literature assessing prevalence rates of depression among Syrian refugees in
developed and developing countries have shown disparities in the ndings. Depression prevalence rates
were reportedly lower in developed countries compared to developing countries, which could be attributed
to the limited capacities of the latter to cope with the needs of these vulnerable populations. In Germany,
depression was detected in close to 14.5% of a Syrian refugee sample (Georgiadou et al., 2018), as
opposed to 37.4% in Turkey (Acarturk et al., 2018), and 43% in Lebanon (Naja et al., 2016).

Previous research suggests that despite the harsh conditions that Syrian refugees often experience, some
key post-displacement variables may act as protective factors, may buffer the severity and incidence of
mental health conditions, and may contribute to posttraumatic growth (Georgiadou et al., 2018; Taher &
Allan, 2020). For instance, obtaining a visa or residence permission, residing in acceptable living
conditions, receiving nancial support, and having access to social and healthcare services, among
others, have contributed to better mental health outcomes (Georgiadou et al., 2018). Rightfully so,
 ndings have con rmed that besides the existing acute and chronic stressors, the mental health of
                                                   Page 3/25
refugees largely depends on the social, economic, and cultural environments associated with their pre
and post-displacement experiences (Porter & Haslam, 2005). However, the status of Syrian refugees in
Lebanon is far from being ideal, with potential protective factors being compromised and minimally
available (Kerbage et al., 2020). As an example, Syrian refugees have restricted rights in Lebanon, which
limit their access to proper healthcare, education, and employment opportunities, due to the lack of a
clearly de ned legal and administrative framework under which they can operate (Blanchet, Fouad, &
Pherali, 2016; Kerbage et al., 2020). Such systemic precariousness excludes potential opportunities for
long-term integration, and places Syrian refugees in Lebanon at increased risk of developing mental
health problems (Jayawickreme et al., 2017; Killikelly, Bauer, & Maercker, 2018). In addition to that, Syrian
refugees lack basic needs such as food, water, and shelter. Their acculturation is also compromised, as
they tend to experience discrimination resulting from the strained Lebanese-Syrian relations due to host
community fatigue with their protracted presence, largely due to job competition and exhaustion of
resources and services (UNHCR, 2019). This discrimination is also manifested as part of the larger socio-
political climate in which continuous pressures are being exerted on Syrian refugees that threaten their
physical, nancial, and social security (Kerbage et al., 2020; Mourtada, Schlecht, & Dejong, 2017; Sim,
Bowes, & Gardner, 2019).

Finally, the lack of sustained funding for mental health services, the fragmented mental healthcare
system, and the scarcity of research make it extremely di cult to understand and respond to the
psychosocial needs of refugees. Syrian refugees, being a high-risk group, have unique psychosocial
needs that should be clearly addressed by mental health workers, based on evidence-driven and
culturally-sensitive ndings. That said, concerted efforts have been made by the National Mental Health
Program (NMHP) at the Ministry of Public Health (MoPH) in Lebanon in collaboration with other
healthcare and humanitarian actors to address this problem (Chammay, Kheir, & Alaouie, 2013; El
Chammay & Ammar, 2014; El Chammay, Karam, & Ammar, 2016; E. Karam et al., 2016). Since the
inception of the Mental Health and Substance Use Strategy for Lebanon 2015–2020, the MoPH has
worked on integrating mental health services into the primary healthcare centres (PHCs) by training
healthcare workers on the Mental Health Gap Action Program (mhGAP) to enhance access to mental
health care (MoPH, 2015). In addition, the MoPH established the Mental Health and Psychosocial
Support Task Force (MHPSS-TF) in collaboration with the World Health Organization (WHO) and the
UNICEF to coordinate the work of over 62 actors on the mental health and psychosocial support within
the Syrian crisis response in Lebanon (E. Karam et al., 2016). This has increased the e ciency and
effectiveness of efforts targeting this problem.

In this context and despite the established initiatives, to our knowledge, there are limited large-scale
studies on the prevalence of depression and its correlates among adult Syrian refugees in the Middle
East. In fact, despite the urgency of the crisis, according to a recent systematic review, only six studies
emanating from a con ict-affected low-to middle-income country were conducted in the Middle East to
assess the prevalence rates of mental health disorders among refugees (Morina, Akhtar, Barth, &
Schnyder, 2018). Clearly, there is an immense need for further research on the mental health of Syrian

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refugees in this region to better understand the associated risk factors, and to support the development
and implementation of global mental health policies addressing this population (Morina et al., 2018).

The present study aims to examine the prevalence rates of depression symptoms and their
sociodemographic and clinical correlates among Syrian refugees in Lebanon. This study also aims to
provide researchers, policy makers, and practitioners with a comprehensive understanding of depression
among migrating populations, which would constitute a foundational base for future interventions and
related programs and policies.

2. Methods
2.1 Design & Population

Our study is a secondary analysis of de-identi ed data from the “Sijilli” (Electronic Health Records (EHR)
for Refugees) database (Saleh, El Arnaout, Faulkner, & Sayegh, 2019). The Sijilli database includes data
on 10,082 Syrian refugees in Lebanon, collected between July 2018 and January 2020 through primary
 eld-based data collection conducted by the Global Health Institute at the American University of Beirut in
partnership with Epic Systems Corporation. Data collection took place in different informal tented
settlements for refugees across Lebanon, covering the Bekaa, North Lebanon, Beirut/Mount Lebanon, and
South Lebanon areas. The sample size in each of these locations was proportionate to the overall Syrian
refugee population residing in the latter based on UNHCR data (UNHCR, 2020) and includes 3565 refugee
records (35.4%) from Bekaa, 2657 refugee records (26.4%) from North Lebanon, 2146 refugee records
(21.3%) from Beirut, and 1714 refugee records (17.0%) from South Lebanon. The Sijilli database includes
records of Syrian refugees of all ages, and covers 7 sections: socio-demographic information (e.g. age,
gender, Syrian governorate of origin, location of the settlement, and year of migration to Lebanon), social
and lifestyle habits (e.g smoking, alcohol drinking, and physical exercise), medical and surgical history,
OBGYN conditions, medication use, vaccination history, and mental health screening. The mental health
screening was completed through the Patient Health Questionnaire-9 (PHQ-9). Any mental health disorder
reported by refugees was noted right after PHQ-9 administration. In this study, we only analysed the data
of adult Syrian refugees who were 18 years of age or above (n=3255).

2.2 Measures

From the collected data, we examined sociodemographic variables of age, gender, marital status, country
of origin, move date, location of settlement, and current occupation, and clinical variables of tobacco and
alcohol use, medical conditions such as diabetes, cardiovascular diseases, neurological conditions,
coronary artery diseases, use of psychiatric medication, and mental health conditions. Symptoms of
depression were assessed in two phases using sequential methodology, which included administering the
PHQ-2 followed by the PHQ-9 for those who screen positive on the former. This method has been widely
used and is especially recommended for e cient data collection in con ict settings such as informal
tented settlements (Poole et al., 2020).

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The PHQ-9 includes 9 items rated on 4-point Likert ranging from 0 to 3, and yields a total score ranging
from 0 to 27. The PHQ-9 score may be used as a categorical outcome of no, mild, moderate, moderately
severe, and severe symptoms of depression, or may be used as a continuous score (Kroenke, Spitzer, &
Williams, 2001). This measure screens for symptoms of depression experienced within the last 2 weeks
and has previously shown evidence of validity, reliability, and unidimensionality (Sawaya, Atoui,
Hamadeh, Zeinoun, & Nahas, 2016). In the present study, the PHQ-9 has shown very good reliability, with
an alpha coe cient of 0.856.

2.3 Analysis

All collected data were coded and exported to SPSS v26. Descriptive statistics for sample characteristics
were computed for adults using frequencies and percentages for categorical data. Internal consistency of
the PHQ-9 was testing using Cronbach alpha. Participants who screened positive on the PHQ-2 and PHQ-
9 were selected for further analysis. PHQ-9 score was categorized into no symptoms (0-4), mild (5-9),
moderate (10-14), moderately severe (15-19), and severe (20-27). PHQ-9 categories and average scores,
as well as individual PHQ-9 items were summarized by gender and tested for statistical difference using
the Pearson’s Chi-Square and the independent t-test. Univariate and multivariate logistic regression
models were computed to determine the association of the PHQ-9 categories (mild and lower vs
moderate to severe) with the sample characteristics. Coe cients and standard errors were exponentiated
to produce odds ratios and 95% con dence intervals. All analyses were run at the 0.05 statistical
signi cance level.

3. Results
3.1 Participants

A total of n = 3255 adult Syrian refugees were included in this study, and their characteristics are
presented in Table 1. The mean age was 36.35 with a standard deviation of 13.87. Most of the
participants were women (67.1%), married (78.4%), had moved to Lebanon between 2012 and 2015
(62.6%),3.2 Prevalence and Distribution of Depression Symptoms originating from Hama governorate in
Syria (18.9%), currently residing in the Bekaa governorate in Lebanon (32.6%), and unemployed (74.6%).
The majority of participants reported never using tobacco (67.6%) and alcohol (99.5%), and only 1.2%
reported using psychiatric medication such as antidepressants, antipsychotics, and anxiolytics. The most
commonly reported medical condition was hypertension (10%), and the presence of any mental health
condition was reported among only 2.1% of the study population.

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Table 1
Characteristics of the present sample (N = 3255)

                                N (%)


Female                          2184    67.1%

Male                            1071    32.9%

Age (mean & SD)                 36.53 (13.87)

18–25                           825     25.3%

26–35                           878     27.0%

36–45                           772     23.7%

> 45                            780     24.0%

Marital Status

Married                         2553    78.4%

Single                          552     17.0%

Divorced                        32      1.0%

Widowed                         106     3.3%

Separated                       12      0.4%

City of Origin

Hama                            616     18.9%

Aleppo                          606     18.6%

Raqqa                           515     15.8%

Idlib                           498     15.3%

Homs                            456     14%

Deir ez-Zor                     299     9.2%

Others                          262     8.0%

Move Date

< 2011                          616     18.9%

2012–2015                       2039    62.6%

                   Page 7/25

2016–2020                        600     18.4%


Beirut                           670     20.6%

Bekaa                            1062    32.6%

North Lebanon                    942     28.9%

South Lebanon                    581     17.8%

Current Occupation

Unemployed                       2420    74.6%

Employed                         826     25.4%


Yes                              611     20.80%

No                               2328    79.20%

Tobacco Use

No use                           2109    67.6%

Ex-user                          91      2.9%

Current                          920     29.5%

Hookah                           171     5.30%

Cigar                            46      1.40%

Cigarettes                       797     24.50%

Alcohol Use

Yes                              17      0.50%

No                               2992    99.50%

Medication Use (Psychiatric)

Psychiatric Medication           39      1.2%

Antidepressant                   28      0.9%

Antipsychotic                    9       0.3%

Anxiolytic                       7       0.2%

Medical Conditions
                     Page 8/25

                             Hypertension                     326      10.0%

                             Neurological disorders           196      6.0%

                             Diabetes                         185      5.7%

                             Cardiovascular Disease           175      5.4%

                             Coronary Artery Disease          62       1.9%

                             Mental Health Conditions

                             Any Mental Condition             40       1.23%

[Insert Table 1 – Characteristics of the sample]
3.2 Prevalence and Distribution of Depression Symptoms

Of those n = 3255 adults, almost a quarter (n = 546) screened positive on the PHQ-9, indicating a 25%
probable prevalence of MDD in the total population. Over half of the sample 51.6% (n = 1678) completed
the full PHQ-9 and were subsequently included in the analysis. The remaining half (n = 1464) were
excluded for screening negative on the PHQ-2. More than half (57.3%) of those who completed the PHQ-9
showed no or mild depression symptom severity, however, the rest (42.7%) showed moderate to severe
symptom severity. The highest reported symptom severity was for “feeling little interest and pleasure in
doing things that used to be enjoyable”, “feeling down and depressed on most days”, and “having little
energy to complete daily tasks”. Whereas the least reported symptoms were for “moving or speaking very
slowly”, and “having suicidal thoughts”.

Women scored signi cantly higher than men on the total PHQ-9 (p = 0.003) and on several of its items,
such as having low energy (p < 0.001), feeling bad (p = 0.036), having concentration di culties (p = 0.06),
and experiencing suicidal thoughts (p = 0.001). In addition, results showed that depression symptoms
affected women’s personal, vocational, and social functions signi cantly more than compared to men (p
= 0.001).

[Insert Table 2 – Distribution of depression symptoms across gender]

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Table 2
                          Distribution of Depression Symptoms N = 1678
                               Female (N = 1215)     Male (N = 463)   Total (N = 1678)    p-value

                               N        %            N       %        N           %

Depression Symptoms

No symptoms (0–4)              184      15.1%        101     21.8%    285         17.0%

Mild (5–9)                     485      39.9%        191     41.3%    676         40.3%

Moderate (10–14)               291      24.0%        91      19.7%    382         22.8%

Moderately Severe (15–19)      161      13.3%        50      10.8%    211         12.6%

Severe (20–27)                 94       7.7%         30      6.5%     124         7.4%    .007

Mean (SD)                      10.1 (5.7)            9.2 (5.7)        9.8 (5.7)           .003

Depression Screening

Mild and lower (0–9)           669      55.1%        292     63.1%    961         57.3%

Moderate to Severe (10–27)     546      44.9%        171     36.9%    717         42.7%   .003

PHQ1: Interest/pleasure

Not at all                     96       8.0%         40      8.7%     136         8.2%

Several days                   614      50.9%        235     51.3%    849         51.0%

More than half of days         293      24.3%        102     22.3%    395         23.7%

Nearly everyday                204      16.9%        81      17.7%    285         17.1%   .815

PHQ2: Down, depressed

Not at all                     43       3.5%         22      4.8%     65          3.9%

Several days                   590      48.7%        236     51.1%    826         49.3%

More than half of days         334      27.6%        110     23.8%    444         26.5%

Nearly everyday                245      20.2%        94      20.3%    339         20.3%   .329

PHQ3: Sleep

Not at all                     335      27.8%        141     30.8%    476         28.6%

Several days                   429      35.6%        167     36.5%    596         35.8%

More than half of days         276      22.9%        93      20.3%    369         22.2%

Nearly everyday                166      13.8%        57      12.4%    223         13.4%   .466

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Female (N = 1215)    Male (N = 463)   Total (N = 1678)   p-value

PHQ4: Energy

Not at all                  142     11.8%        103    22.4%     245      14.7%

Several days                524     43.4%        192    41.7%     716      42.9%

More than half of days      344     28.5%        104    22.6%     448      26.9%

Nearly everyday             198     16.4%        61     13.3%     259      15.5%     < .001

PHQ5: Appetite

Not at all                  502     41.4%        212    46.0%     714      42.7%

Several days                383     31.6%        137    29.7%     520      31.1%

More than half of days      206     17.0%        65     14.1%     271      16.2%

Nearly everyday             121     10.0%        47     10.2%     168      10.0%     .289

PHQ6: Feeling bad/failure

Not at all                  452     37.6%        194    42.7%     646      39.0%

Several days                423     35.2%        163    35.9%     586      35.4%

More than half of days      212     17.6%        55     12.1%     267      16.1%

Nearly everyday             116     9.6%         42     9.3%      158      9.5%      .036

PHQ7: Concentrating

Not at all                  477     39.5%        215    46.5%     692      41.4%

Several days                387     32.0%        134    29.0%     521      31.2%

More than half of days      236     19.5%        76     16.5%     312      18.7%

Nearly everyday             109     9.0%         37     8.0%      146      8.7%      .069

PHQ8: Move/speak slowly

Not at all                  648     53.8%        261    57.5%     909      54.8%

Several days                343     28.5%        124    27.3%     467      28.1%

More than half of days      154     12.8%        48     10.6%     202      12.2%

Nearly everyday             60      5.0%         21     4.6%      81       4.9%      .496

PHQ9: Better off dead

Not at all                  730     60.4%        324    70.9%     1054     63.3%

Several days                264     21.8%        77     16.8%     341      20.5%
                                        Page 11/25
Female (N = 1215)     Male (N = 463)    Total (N = 1678)   p-value

   More than half of days          131      10.8%        30     6.6%       161      9.7%

   Nearly everyday                 84       6.9%         26     5.7%       110      6.6%      .001

   PHQ10 Effect work/people

   Not di cult at all              384      32.4%        191    42.6%      575      35.2%

   Somewhat di cult                504      42.5%        166    37.1%      670      41.0%

   Very di cult                    205      17.3%        58     12.9%      263      16.1%

   Extremely di cult               93       7.8%         33     7.4%       126      7.7%      .001

3.3 Sociodemographic and Clinical Correlates of Depression Symptoms
Based on the results of the rst regression model at the bivariate level, being of older age (OR 1.01, 95%
CI 1.00-1.02), a woman (OR 1.39, 95% CI 1.12–1.74), divorced/separated (OR 3.75, 95% CI 1.80–7.85), on
psychiatric medication (OR 2.54, 95% CI 1.07–6.04), having hypertension (OR 1.37, 95% CI 1.02–1.83) or
any nervous-system related disorder (OR 1.82, 95% CI 1.24–2.66), or mental health condition (OR 5.20,
95% CI 2.37–11.42) signi cantly increased the odds for showing more severe symptoms of depression.
There was also a trend for a longer period of stay in Lebanon, which was found to increase the odds of
showing more severe symptoms of depression. On the other hand, informal tented settlement location,
current occupation, tobacco and alcohol use, and having diabetes or CVDs showed no statistically
signi cant association with symptoms of depression.
[Insert Table 3 – bivariate level of analysis]

                                                Page 12/25
Table 3
          Sociodemographic and Clinical Correlates of Depression Symptoms at the Bivariate
                                         Level (N = 1678)
         Risk Factor                          N %          p-valueOdds RatioLower LUpper L
         Age (continuous)
         Mean (SD)
         Mild and Lower PHQ                        38.2 (12.93)
         Moderate-severe PHQ                       40.1 (13.24).003 1.011        1.004 1.019
         Male                                      171 36.9%          ref
         Female                                    546 44.9% .003 1.394          1.118 1.737
         Marital Status
         Married                                   563 40.9%          ref
         Single                                    87 45.3%           1.196      .883    1.621
         Widowed                                   41 55.4%           1.794      1.120 2.873
         Divorced/separated                        26 72.2% < .001 3.755         1.796 7.847
         Period of Stay (pre 2011 vs post 2011)
         Mild and Lower PHQ                        4.9 (2.5)
         Moderate-severe PHQ                       5.1 (3.2)    .085 .970        .938    1.004
         Period of Stay (continuous)
         Mean (SD)
         Mild and Lower                            4.7 (2.1)
         Moderate-severe                           4.7 (2.1)    .941 1.002       .956    1.049
         Beirut                                    129 39.2%          ref
         North                                     193 42.6%          1.151      .862    1.537
         South                                     96 42.1%           1.128      .800    1.590
         Bekaa                                     299 44.8% .418 1.256          .960    1.644
         Current Occupation
         Employed                                  165 41.7%          ref
         Not Employed                              549 43.0% .633 1.057          .841    1.329
         Tobacco Use
         Never User                                461 42.9%          ref
         Current                                   239 43.2% .897 1.014          .824    1.247
         Alcohol Use
         No                                        686 43.7%          ref
         Yes                                       3    42.9% .966 .968          .216    4.337
         Psychiatry Meds Use
         No                                        702 42.4%          ref
         Yes                                       15 65.2% .028 2.545           1.073 6.037
         Medical Conditions
         Diabetes No                               659 42.2%
         Diabetes Yes                              58 49.2% .144 1.322           .909    1.922
         Hypertensive no                           614 41.8%
         Hypertensive yes                          103 49.5% .034 1.368          1.022 1.829
         CVD No                                    666 42.3%
         CVD Yes                                   51 48.6% .211 1.286           .866    1.910
         Nervous D No                              652 41.7%
         Nervous D Yes                             65 56.5% .002 1.816           1.240 2.662
         Mental health No                          687 41.9%
         Mental Health Yes                         30 78.9% < .001 5.202         2.370 11.417
At the multivariate level of analysis, comparable results were obtained, whereby being ≥ 45 of age (OR
1.70, 95% CI 1.22–2.36), a woman (OR 1.35, 95% CI 1.08–1.70), divorced/separated (OR 3.32, 95% CI
                                                Page 13/25
1.57–7.01), reporting a neurological disorder (OR 1.77, 95% CI 1.20–2.62) or a mental health condition
(OR 5.30, 95% CI 2.40-11.67) signi cantly increased the odds of screening positive for MDD. However,
unlike the bivariate model, being on psychiatric medication and presenting with hypertension were not
signi cantly associated with the increased odds of depression severity symptoms.
[Insert Table 4 – multivariate level of analysis]
                                                Table 4
                          Sociodemographic and Clinical Correlates of Depression
                              Symptoms at the Multivariate Level (N = 1678)
                     Risk Factor        B    SE p-valueOdds RatioLower LUpper L
                     Age groups
                     18–25 (ref)
                     26–35              .274 .165.097 1.315           .951   1.818
                     36–45              .223 .166.178 1.250           .903   1.730
                     > 45               .530 .167.002 1.699           1.224 2.360
                     Male (ref)
                     Female             .302 .116.009 1.353           1.077 1.698
                     Marital Status
                     Married (ref)
                     Single             .253 .161.116 1.288           .939   1.766
                     Widowed            .393 .249.115 1.481           .909   2.413
                     Divorced/Separated1.201.381.002 3.324            1.575 7.015
                     Medical Conditions
                     Nervous D NO
                     Nervous D YES      .573 .198.004 1.774           1.203 2.616
                     Mental Health No
                     Mental health YES 1.667.403< .001 5.297          2.405 11.668
4. Discussion
To our knowledge, this is one of the very few regional, and the only national large-scale study addressing
the mental health of a representative sample of adult Syrian refugees in Lebanon and is therefore a
valuable contribution to the literature. In the present study, we report on the prevalence of depression
symptoms, which represent one of the most common and debilitating mental health disorders among
Syrian refugees, and we explore their sociodemographic and clinical correlates.

As expected, the prevalence of depression symptoms among the study population was high, with an
estimated one in four refugees meeting criteria for MDD. Positive PHQ-9 screening and consequently,
probable MDD, was detected in 25% of the study population, which is considerably higher than
depression rates (9.9%) previously reported among the general population in Lebanon (E. G. Karam et al.,
2008). Our ndings contrast a previous study that used the same depression measure on Syrian refugees
in Germany, and in which only 14% of their sample screened positive for MDD (Georgiadou et al., 2018).
One of the main ndings of that study was that post-migration conditions and future positive prospects
in host countries may be protective against mental health disorders among these populations
(Georgiadou et al., 2018). Indeed, this could explain the discrepancy between their ndings and ours,
considering that post-migration factors in Lebanon are poor and may ultimately present important risk
factors instead of being protective against mental health disorders (Kerbage et al., 2020).

                                                    Page 14/25
In Lebanon, many post-migration variables present important obstacles towards adequate health and
survival. For example, the high prevalence rates of depression symptoms could be attributed to numerous
external factors beyond their exposure to traumatic events, such as the di cult conditions in which
Syrian refugees live, the limited opportunities for development, and the many challenges associated with
their social integration and acculturation (Kerbage et al., 2020). Additionally, the constant internal and
regional socioeconomic and political con icts promote little hope for refugees to settle in a stable context
unless they travel to more developed countries, which is a solution Syrian refugees commonly request to
overcome their documented adverse living conditions (Kerbage et al., 2020). The existing economic
di culties in Lebanon, which are now exponentially compounded by the fall of Lebanese pound
(Youssef, 2020), and by the colossal explosion that devastated the capital Beirut in August 2020 (Tharoor,
2020), may place Syrian refugees under further instability and vulnerability. With that said, the situation is
currently expected to be worse in terms of mental health outcomes, considering the COVID-19 pandemic,
which has restricted mobility, tremendously challenged the attainment of basic survival needs, induced
added stress, and further limited opportunities for work and social interactions (Whaibeh, Mahmoud, &
Naal, 2020).

In response to the Syrian crisis, the MoPH in collaboration with the Ministry of Social Affairs and with
local and international non-governmental organizations (NGOs) have been providing free-of-charge
primary healthcare services, including mental health services, for UNHCR-registered Syrian refugees. Yet,
due to limited nancial capacities, these efforts have been reportedly unable to meet the increasing needs
of these vulnerable populations (Masri & Srour, 2014; Noubani et al., 2020). The situation is even worse
for unregistered refugees who have restricted capacities to receive the appropriate healthcare support
(Masri & Srour, 2014). Despite these efforts, the rates of depression remain high, as indicated by our
 ndings. Although mental health services and psychosocial interventions may induce relief of depression
severity over the short-term, long-term improvements may require complementary macro-level changes in
the living conditions of refugees, their legal status, and the need to foster positive future prospects.

It is also possible that mental health services are not reaching enough refugees. Notwithstanding the
value of the provided services, Syrian refugees cite many barriers to seeking mental health services in
Lebanon, including lack of trust in and limited knowledge of available services, limited mental health
literacy and perceived need for treatment, lack of services especially in rural areas, associated di culties
in commuting, nancial barriers and lack of mental health coverage, and social stigma which may
impede refugees seeking healthcare fearing of shame and discrimination (Noubani et al., 2020).
Furthermore, due to pervasive cultural beliefs, Syrian refugees tend to seek religious healers as a rst line
of treatment for mental illness given their perceived cultural appropriateness and their reduced
association with social stigma when compared to mental health professionals (Al Laham et al., 2020).

Despite high depression rates in our sample, our ndings are favourable in comparison to the last study
that evaluated the prevalence of depression among adult Syrian refugees in Lebanon 5 years ago, in
which a depression prevalence rate of 43.9% was reported (Naja et al., 2016). Although some important
limitations may prohibit this comparison, such as their reliance on a clinical diagnosis as opposed to
                                                  Page 15/25
using a screening instrument, and their smaller sample size (n = 310) (Naja et al., 2016), our ndings may
point towards an overall improvement. However, this could also be a result of the different sample
characteristics, considering that Naja et al (2016)’s study represented refugees seeking social and
healthcare services from two non-governmental organizations, whereas ours included a randomly
selected representative sample of participants from the general population of Syrian refugees across
Lebanon; under these different contexts, our sample would be expected to score lower on depression.

In terms of its correlates, our ndings show that age, gender, and marital status are strongly associated
with an increased risk for MDD. We found that older age is associated with higher risk of depression,
which contrasts previous ndings showing an inverse relationship (Georgiadou et al., 2018), or no
correlation (Naja et al., 2016; Poole et al., 2018) between these variables. In speci c, individuals over
45 years of age are at highest risk of developing depression, and this may be a result of several
contributing factors. From a social perspective, older individuals in the Arab region are regarded as pillars
of their families, and they tend to hold leadership roles in their communities (Bazzi & Chemali, 2016;
Chemali, Borba, Johnson, Khair, & Fricchione, 2018). Previous research suggests that as a result of the
war, this community role may be disrupted, impacting familial connectedness and social ties, and
bringing along feelings of isolation and inadequacy (Chemali et al., 2018). From a clinical perspective,
older individuals often have pre-existing and chronic conditions which may warrant further medical
attention. In this regard, unmet healthcare needs due to the limited resources in these communities may
further aggravate their mental health conditions and general well-being. Finally, comorbidities between
cognitive disorders and depression may be more pronounced and severe among this age group, which
may impact their well-being and overall functionality (Adams & Moon, 2009).

In terms of gender differences, previous research consistently reported higher prevalence rates of
depression among women compared to men across studies among the general population, and this is
also true of research among Syrian refugees (Georgiadou et al., 2018; Poole et al., 2018) congruent with
our ndings. Although some of the same justi cations that have been previously cited in the literature
may still be used to explain these gender-based variations, other explanations that are speci c to Syrian
refugees in Lebanon should be considered. For example, women in refugee settings tend to be subjected
to early and forced marriage and bear family responsibilities at an early age, in addition to being exposed
to sexual harassment and violence in the household and community at large (Noubani et al., 2020), all of
which are potential stressors that increase the risk of developing MDD. Also, these women allude to child
rearing and associated responsibilities as important sources of stress and anxiety, especially when
considering their worries about the discrimination and bullying their children may face in schools in
Lebanon (Noubani et al., 2020). Additionally, upon further scrutiny, and although the severity of
depression symptoms was comparable among both genders, our ndings indicate that women were
signi cantly more likely to report feeling down, having lower energy, and having more suicidal thoughts
compared to men, which is consistent with previous ndings (Kim et al., 2015). Women were also more
likely to report having their level of function in social, vocational, and self-care areas adversely affected
by depression symptoms compared to men.

                                                   Page 16/25
The association between marital status and depression has been previously examined among Syrian
refugees, whereby being married was found to be protective against depression in one study, potentially
due to its association with social support (Poole et al., 2018), and where no relationship was found in
others (Acarturk et al., 2018; Georgiadou et al., 2018; Naja et al., 2016). In our study, being divorced or
separated increased the odds of having depression, but this was not the case for being single or
widowed. This means that the experience of going through a divorce or separation in this community
could place individuals at higher risk of having depression than if they were single or had lost their

On the other hand, several variables were found not to be related to depression, most importantly the
location of the informal tented settlement and the period of stay in Lebanon. It is possible that the
properties of the four examined informal tented settlements for refugees in Lebanon entail similar living
conditions that are below the appropriate standards and share similarity in terms of the availability of
support and healthcare services, which translate into poor mental health among their residents. As for the
period of stay in Lebanon, although previous studies suggested that a longer period of stay is associated
with higher risk of depression (Poole et al., 2018), in our study we only found a non-statistically
signi cant trend con rming this association at the bivariate level; however, no association was observed
at the multivariate level. These ndings suggest that the period of stay in Lebanon is not correlated with
the risk of developing depression, given that the mental health of Syrian refugees may be equally
compromised among newcomers and long-term residents. That said, arriving in Lebanon before and after
the breakout of the Syrian war in 2011 was accounted for in the study analysis, and no signi cant
differences in depression scores were observed.

In terms of the clinical characteristics, we found that reporting a neurological condition or a history of
mental illness increased the risk of depression, presumably because mental illness is directly related to
depression symptoms, and neurological conditions are frequently comorbid with depression (Bulloch et
al., 2015). On the other hand, diabetes, CVDs and coronary artery diseases were not found to be risk
factors for depression, although these have been associated with depression in previous studies (Elderon
& Whooley, 2013; Mezuk, Eaton, Albrecht, & Golden, 2008). Similarly, although reporting hypertension and
the use of psychiatric medication have shown a statistically signi cant association with depression at
the bivariate level of analysis, this was not replicated at the multivariate level. This means that unlike
neurological conditions, non-communicable diseases may not be signi cant risk factors for developing
depression among Syrian refugees in Lebanon. Possibly, these associations might be clouded by the
overall high rates of depression in the study population.

5. Recommendations & Implications
Our ndings indicate that depression prevalence rate among Syrian refugees in Lebanon is high. In light
of this, an increase in screening efforts and referral mechanisms to PHCs and other health facilities is
highly needed to improve access to mental health services and to reduce depression rates. According to a
recent national facility assessment, almost 32% of PHCs in Lebanon are currently delivering mental
                                                   Page 17/25
health services following the mhGAP training, and almost 50% of them cover rural areas (Hemadeh,
Kdouh, Hammoud, Jaber, & Khalek, 2020), where most refugees reside. The integration of telemental
health services into PHCs, community-based organizations, and other healthcare facilities that could be
accessed by refugees may be a suitable option to enhance the reach of these services (N Almoshmosh,
Jefee-Bahloul, Abdal- lah, & Barkil-Oteo, 2020; Naal, Whaibeh, & Mahmoud, 2020). Telemental health
services have strong potential in overcoming traditional barriers to mental health service use such as
transportation challenges, unequal distribution of specialists among others, and may enhance access to
services (Naal et al., 2020). Importantly, considering the mobility restrictions brought forth by the COVID-
19, telemental health adheres to the social distancing requirements, and enables access to mental health
services for remote and underserved populations (Whaibeh et al., 2020). PHCs in Lebanon are usually
equipped with the minimally required technological hardware and software needed for that, they tend to
have minimally available specialized mental health care services, and their catchment areas tend to reach
rural and underserved populations (Hemadeh et al., 2020). To that end, special attention should be given
to high-risk groups such as older adults, women, and divorced/separated individuals, particularly those
with a history of neurological or mental health conditions. More importantly, using a culturally-sensitive
approach, efforts to combat social stigma and improve mental health literacy in these communities are
necessary to encourage treatment seeking when available. For example, one recent qualitative study
suggested that collaborations between mental health professionals and community religious healers
may be a key factor to creating pathways for referrals to mental health services (Al Laham et al., 2020).
Additionally, it is also important to provide minimally required and essential resources for survival, in
parallel as a complement to the existing mental health services. In this regard, different aids that improve
the living conditions and the quality of life for Syrian refugees are crucial, especially those that have been
consistently identi ed as key protective factors. For example, providing options to 1) improve the
 nancial situation in order for them to be able to meet their basic survival needs, 2) facilitate interactions
with host communities and reduce tensions, and 3) improve the legal status of refugees, which help them
bene t from the available services.

6. Limitations
Some limitations should be considered in light of our ndings. First, it is important to note that the study
population is not entirely homogeneous because it included individuals who came before and after the
breakout of the Syrian war in 2011, which implies different levels of exposure to war trauma.
Nevertheless, we accounted for this in our analysis by comparing depression symptoms between both
groups whereby no signi cant differences in symptom severity were observed. Second, biases such as
social desirability may have in uenced the collected data (e.g. symptoms of depression, alcohol use,
employment etc.) since participants were administered the questionnaire through in-person interviews
rather than by self-reported means, given the high levels of reported illiteracy in informal tented
settlements. Third, pre-and post- migration data such as legal status, household and living conditions,
and the quality of healthcare provision among others were not collected, which could otherwise have
provided a clearer association between migration status and depression. Lastly, reliance on self-reported

                                                  Page 18/25
data rather than o cial diagnostic reports may have resulted in under- or overestimation of the reported
health conditions.

7. Conclusion
Mental health is of growing importance in refugee populations due to the increased vulnerability of these
populations to mental health disorders. Our study ndings revealed high rates of depression symptoms
among the study population, with one in four refugees meeting criteria for probable MDD. Furthermore,
we found an association between potential risk factors such as, being of older age, a woman,
divorced/separated, having a neurological condition or a history of mental illness and the increased odds
of having depression symptoms. Our ndings bear important public health and clinical implications on
refugee health, and call for the enhancement of screening efforts, the need to improve access and referral
to mental health services, and the importance of improving post-migration factors such as those related
to living conditions, acculturation, and legal status.

AUB: American University of Beirut

COVID-19: Corona Virus Diseases – 19

GHI: Global Health Institute

IRB: Institutional Review Board

MDD: Major Depressive Disorder

mhGAP: Mental Health Gap Action Program

MHPSS-TF: Mental Health and Psycho Social Support – Task Force

MoPH: Ministry of Public Health

NMHP: National Mental Health Program

PHC: Primary Healthcare Center

PHQ-9: Patient Health Questionnaire – 9

PTSD: Post Traumatic Stress Disorder

WHO: World Health Organization

                                                   Page 19/25

We wish to thank the following NGOs that facilitated access to the refugees across Lebanon to complete
data collection of the Sijilli EHR: Malaak, Makhzoumi Foundation, and Beyond Association. We wish to
also thank the volunteer health professionals who were involved in data collection including Dr. Lara
Nahouli, Dr. Ghaidaa El Saddik, Mr. Mohamad Jamal Obeid, Mr. Abdul Ghani Abou Koura, Mr. Mohamad
Najdi, and Mr. Nader Husseini.

Authors’ Contributions:

The study was designed and conceptualized by HN, NEA, DN, and SS. HN wrote the rst draft, and
contributed to data analysis and nal revisions. NEA coordinated the overall project, contributed to writing
the methodology, and edited the manuscript. DN contributed to data analysis, review, and editing of the
manuscript. LA performed revisions and editing of the manuscript. HD conducted full data analysis,
wrote parts of the methodology section, and edited the manuscript. RH provided support for data
management and data analysis and edited the draft. SS reviewed and provided critical comments on the
manuscript. All authors reviewed and approved the nal version.


This research did not receive any nancial support.

Availability of the data and materials:

The data can be made available following reasonable request to the corresponding author.

Ethics approval and consent to participate:

The present study was approved by the Institutional Review Board at the American University of Beirut.
Informed consent was submitted by all subjects when they were enrolled.

Consent for publication:

Not applicable.

Competing interests:

The authors declare that they have no competing interests

  1. Abou-Saleh, M. T., & Hughes, P. (2015). Mental health of Syrian refugees: looking backwards and
    forwards. The Lancet. Psychiatry, 2(10), 870–871.

                                                Page 20/25
2. Acarturk, C., Cetinkaya, M., Senay, I., Gulen, B., Aker, T., & Hinton, D. (2018). Prevalence and predictors
    of posttraumatic stress and depression symptoms among syrian refugees in a refugee camp.
   Journal of Nervous and Mental Disease, 206(1), 40–45.
 3. Adams, K. B., & Moon, H. (2009). Subthreshold depression: Characteristics and risk factors among
   vulnerable elders. Aging and Mental Health, 13(5), 682–692.
 4. Al Laham, D., Ali, E., Mousally, K., Nahas, N., Alameddine, A., & Venables, E. (2020). Perceptions and
   Health-Seeking Behaviour for Mental Illness Among Syrian Refugees and Lebanese Community
   Members in Wadi Khaled, North Lebanon: A Qualitative Study. Community Mental Health Journal,
   56(5), 875–884.
 5. Almoshmosh, N., Jefee-Bahloul, H., Abdal- lah, W., & Barkil-Oteo, A. (2020). Use of store-and-forward
   tele-mental health for displaced Syrians. Intervention, 18(1), 66–70.
 6. Almoshmosh, N., Jefee Bahloul, H., Barkil-Oteo, A., Hassan, G., & Kirmayer, L. J. (2019). Mental health
   of resettled Syrian refugees: a practical cross-cultural guide for practitioners. Journal of Mental
   Health Training, Education and Practice, 15(1), 20–32.
 7. Bazzi, L., & Chemali, Z. (2016). A Conceptual Framework of Displaced Elderly Syrian Refugees in
    Lebanon: Challenges and Opportunities. Global Journal of Health Science, 8(11), 54.
 8. Blanchet, K., Fouad, F. M., & Pherali, T. (2016). Syrian refugees in Lebanon: The search for universal
   health coverage Mr Ruwan Ratnayake. Con ict and Health, 10(1), 1–5.
 9. Bulloch, A. G. M., Fiest, K. M., Williams, J. V. A., Lavorato, D. H., Berzins, S. A., Jetté, N., … Patten, S. B.
   (2015). Depression - A common disorder across a broad spectrum of neurological conditions: A
   cross-sectional nationally representative survey. General Hospital Psychiatry, 37(6), 507–512.
10. Chammay, R. El, Kheir, W., & Alaouie, H. (2013). Assessment of mental health and psychosocial
   support services for Syrian refugees in Lebanon. Unhcr, (December), 1–68.
11. Chemali, Z., Borba, C. P. C., Johnson, K., Khair, S., & Fricchione, G. L. (2018). Needs assessment with
    elder Syrian refugees in Lebanon: Implications for services and interventions. Global Public Health.
12. Doocy, S., Sirois, A., Tileva, M., Storey, J. D., & Burnham, G. (2013). Chronic disease and disability
   among Iraqi populations displaced in Jordan and Syria. International Journal of Health Planning and
   Management, 28(1), 1–12.
13. El Arnaout, N., Rutherford, S., Zreik, T., Nabulsi, D., Yassin, N., & Saleh, S. (2019). Assessment of the
   health needs of Syrian refugees in Lebanon and Syria’s neighboring countries. Con ict and Health,
   13(1), 1–14.

                                                    Page 21/25
14. El Chammay, R., & Ammar, W. (2014). Syrian crisis and mental health system reform in Lebanon. The
   Lancet, 384(9942), 494.
15. El Chammay, R., Karam, E., & Ammar, W. (2016). Mental health reform in Lebanon and the Syrian
   crisis. The Lancet Psychiatry, 3(3), 202–203.
16. Elderon, L., & Whooley, M. A. (2013). Depression and cardiovascular disease. Progress in
   Cardiovascular Diseases, 55(6), 511–523.
17. Georgiadou, E., Zbidat, A., Schmitt, G., & Erim, Y. (2018). Prevalence of Mental Distress Among Syrian
   Refugees With Residence Permission in Germany: A Registry-Based Study. Frontiers in Psychiatry,
   9(393), 1–12.
18. Hassan, G., Ventevogel, P., Jefee-Bahloul, H., Barkil-Oteo, A., & Kirmayer, L. J. (2016). Mental health
   and psychosocial wellbeing of Syrians affected by armed con ict. Epidemiology and Psychiatric
   Sciences, 25(2), 129–141.
19. Hemadeh, R., Kdouh, O., Hammoud, R., Jaber, T., & Khalek, L. (2020). The primary health care network
    in Lebanon: a national facility assessment Randa. Eastern Mediterranean Health Journal, 1–9.
   Retrieved from
20. IHME. (2020). Global Burden of Disease Compare.
21. Jayawickreme, N., Mootoo, C., Fountain, C., Rasmussen, A., Jayawickreme, E., & Bertuccio, R. (2017).
   Post-con ict struggles as networks of problems: A network analysis of trauma, daily stressors and
   psychological distress among Sri Lankan war survivors. Social Science and Medicine, 190, 119–132.
22. Jefee-Bahloul, H., Barkil-Oteo, A., Pless-Mulloli, T., & Fouad, F. M. (2015). Mental health in the Syrian
    crisis: Beyond immediate relief. The Lancet, 386(10003), 1531.
23. Jefee-Bahloul, H., Moustafa, M. K., Shebl, F. M., & Barkil-Oteo, A. (2014). Pilot Assessment and Survey
   of Syrian Refugees’ Psychological Stress and Openness to Referral for Telepsychiatry (PASSPORT
   Study). Telemedicine and E-Health, 20(10), 977–979.
24. Karam, E., El Chammay, R., Richa, S., Naja, W., Fayyad, J., & Ammar, W. (2016). Lebanon: mental
   health system reform and the Syrian crisis. British Journal of Psychiatry, 13(4), 87–89.
25. Karam, E. G., Mneimneh, Z. N., Dimassi, H., Fayyad, J. A., Karam, A. N., Nasser, S. C., … Kessler, R. C.
   (2008). Lifetime prevalence of mental disorders in Lebanon: First onset, treatment, and exposure to
   war. PLoS Medicine, 5(4), 0579–0586.
26. Kerbage, H., Marranconi, F., Chamoun, Y., Brunet, A., Richa, S., & Zaman, S. (2020). Mental Health
   Services for Syrian Refugees in Lebanon: Perceptions and Experiences of Professionals and
   Refugees. Qualitative Health Research, 30(6), 849–864.
27. Killikelly, C., Bauer, S., & Maercker, A. (2018). The assessment of grief in refugees and post-con ict
    survivors: A narrative review of etic and emic research. Frontiers in Psychology, 9(OCT), 1–12.
28. Kim, J. H., Cho, M. J., Hong, J. P., Bae, J. N., Cho, S. J., Hahm, B. J., … Chang, S. M. (2015). Gender
    differences in depressive symptom pro le: Results from nationwide general population surveys in
                                                  Page 22/25
Korea. Journal of Korean Medical Science, 30(11), 1659–1666.
29. Knudsen, A. (2016). Syria’s refugees in Lebanon: brothers, burden, and bone of contention. In
    Lebanon Facing The Arab Uprisings (pp. 135–154). London: Palgrave Pivot.
30. Kroenke, K., Spitzer, R., & Williams, J. (2001). The PHQ-9: Validity of a Brief Depression Severity
    Measure. Journal of General Internal Medicine, 16, 606–613.
31. Lindert, J., Ehrenstein, O. S. vo., Priebe, S., Mielck, A., & Brähler, E. (2009). Depression and anxiety in
    labor migrants and refugees - A systematic review and meta-analysis. Social Science and Medicine,
    69(2), 246–257.
32. Llosa, A. E., Ghantous, Z., Souza, R., Forgione, F., Bastin, P., Jones, A., … Grais, R. F. (2014). Mental
    disorders, disability and treatment gap in a protracted refugee setting. British Journal of Psychiatry,
    204(3), 208–213.
33. Masri, S., & Srour, I. (2014). Assessment of the impact of syrian refugees in lebanon and their
    employment pro le.
34. May, M., & Klonsky, D. (2016). What distinguishes suicide attempters from suicide ideators? A meta-
    analysis of potential factors. Clinical Psychology: Science and Practice, 23, 5–20.
35. Mezuk, B., Eaton, W. W., Albrecht, S., & Golden, S. H. (2008). Depression and type 2 diabetes over the
    lifespan: A meta-analysis. Diabetes Care, 31(12), 2383–2390.
36. MoPH. (2015). Mental Health and Substance Use - Prevention, Promotion, and Treatment: Situation
    Analysis and Strategy for Lebanon 2015-2020 Version 1.1. Beirut: Lebanon.
37. Morina, N., Akhtar, A., Barth, J., & Schnyder, U. (2018). Psychiatric disorders in refugees and internally
    displaced persons after forced displacement: A systematic review. Frontiers in Psychiatry, 9(SEP).
38. Mourtada, R., Schlecht, J., & Dejong, J. (2017). A qualitative study exploring child marriage practices
    among Syrian con ict-affected populations in Lebanon. Con ict and Health, 11(Suppl 1).
39. Naal, H., Whaibeh, E., & Mahmoud, H. (2020). Guidelines for primary health care-based telemental
    health in a low-to middle-income country : the case of Lebanon. International Review of Psychiatry,
    0(0), 1–9.
40. Naja, W. J., Aoun, M. P., El Khoury, E. L., Abdallah, F. J. B., & Haddad, R. S. (2016). Prevalence of
    depression in Syrian refugees and the in uence of religiosity. Comprehensive Psychiatry, 68, 78–85.
41. Noubani, A., Diaconu, K., Ghandour, L., El Koussa, M., Loffreda, G., & Saleh, S. (2020). A community-
    based system dynamics approach for understanding factors affecting mental Health and Health
    seeking behaviors in Beirut and Beqaa regions of Lebanon. Globalization and Health, 16(1), 1–13.

                                                   Page 23/25
42. Poole, D. N., Hedt-Gauthier, B., Liao, S., Raymond, N. A., & Bärnighausen, T. (2018). Major depressive
    disorder prevalence and risk factors among Syrian asylum seekers in Greece. BMC Public Health,
    18(1), 1–9.
43. Poole, D. N., Liao, S., Larson, E., Hedt-Gauthier, B., Raymond, N. A., Bärnighausen, T., & Smith Fawzi,
    M. C. (2020). Sequential screening for depression in humanitarian emergencies: A validation study of
    the Patient Health Questionnaire among Syrian refugees. Annals of General Psychiatry, 19(1), 1–10.
44. Porter, M., & Haslam, N. (2005). Predisplacement and postdisplacement of refugees and internally
    displaced persons. The Journal of the American Medical Association, 294(5), 610–612.
45. Refaat, M., & Mohanna, K. (2013). Syrian refugees in Lebanon: facts and solutions. Lancet, 382,
46. Rogers, M. L., Ringer, F. B., & Joiner, T. E. (2018). The association between suicidal ideation and
    lifetime suicide attempts is strongest at low levels of depression. Psychiatry Research, 270(August),
47. Saleh, S., El Arnaout, N., Faulkner, J. R., & Sayegh, M. H. (2019). Sijilli: a mobile electronic health
    records system for refugees in low-resource settings. The Lancet Global Health, 7(9), e1168–e1169.
48. Sawaya, H., Atoui, M., Hamadeh, A., Zeinoun, P., & Nahas, Z. (2016). Adaptation and initial validation
    of the Patient Health Questionnaire - 9 (PHQ-9) and the Generalized Anxiety Disorder - 7
    Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample. Psychiatry
    Research, 239, 245–252.
49. Sim, A., Bowes, L., & Gardner, F. (2019). The Promotive Effects of Social Support for Parental
    Resilience in a Refugee Context: a Cross-Sectional Study with Syrian Mothers in Lebanon. Prevention
    Science, 20(5), 674–683.
50. Taher, R., & Allan, T. (2020). Posttraumatic Growth in Displaced Syrians in the UK: A Mixed-Methods
    Approach. Journal of Loss and Trauma, 25(4), 333–347.
51. Tharoor, I. (2020). Beirut’s Blast and Lebanon’s Deeper Crisis.
52. UNHCR. (2018). Syria Regional Refugee Response.
54. UNHCR. (2020). Operational Portal: Refugee Situations.
55. Ventevogel, P., Van, O., Schilperoord, M., & Saxena, S. (2015). Improving mental health care in
    humanitarian emergencies. Bulletin of the World Health Organization, 93(10), 666.
56. Weine, S. (2011). Developing Preventive Mental Health Interventions for Refugee Families in
    Resettlement. Family Process, 50, 410–430.

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